Video OCR: indexing digital news libraries by recognition of superimposed captions |
| |
Authors: | Toshio Sato Takeo Kanade Ellen K Hughes Michael A Smith Shin'ichi Satoh |
| |
Affiliation: | (1) Toshiba Corporation, 70 Yanagi-cho, Saiwai-ku, Kawasaki 210-8501, Japan; e-mail: toshio4.sato@toshiba.co.jp , JP;(2) School of Computer Science, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA , US;(3) National Center for Science Information Systems (NACSIS), 3-29-1 Otsuka, Bunkyo-ku, Tokyo 112-8640, Japan , JP |
| |
Abstract: | The automatic extraction and recognition of news captions and annotations can be of great help locating topics of interest
in digital news video libraries. To achieve this goal, we present a technique, called Video OCR (Optical Character Reader),
which detects, extracts, and reads text areas in digital video data. In this paper, we address problems, describe the method
by which Video OCR operates, and suggest applications for its use in digital news archives. To solve two problems of character
recognition for videos, low-resolution characters and extremely complex backgrounds, we apply an interpolation filter, multi-frame
integration and character extraction filters. Character segmentation is performed by a recognition-based segmentation method,
and intermediate character recognition results are used to improve the segmentation. We also include a method for locating
text areas using text-like properties and the use of a language-based postprocessing technique to increase word recognition
rates. The overall recognition results are satisfactory for use in news indexing. Performing Video OCR on news video and combining
its results with other video understanding techniques will improve the overall understanding of the news video content. |
| |
Keywords: | :Digital video library – Caption – Index – OCR – Image enhancement |
本文献已被 SpringerLink 等数据库收录! |
|